Generative engine optimization

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Generative engine optimization (GEO) is the process of improving the visibility, relevance, and presentation of content in response to queries made to generative engines, such as large language models (LLMs).

Unlike SEO, which targets traditional search engine rankings, GEO focuses on how information is surfaced, summarized, or cited by artificial intelligence systems powered by generative models.^[1]

"Generative engine optimization" is not yet a universally accepted name. It is also referred to as "answer engine optimization" (AEO)^[2], "artificial intelligence search optimization"^[3] or artificial intelligence optimization.

History

[edit]

The concept of generative engine optimization emerged in the early 2020s alongside the widespread adoption of generative AI tools such as OpenAI's ChatGPT, Anthropic's Claude, and Google's Gemini.^[1]

Industry applications

[edit]

Marketing: Brands aim to influence how their offerings are presented in AI‑generated summaries or product recommendations.^[1]

References

[edit]

^ ^a ^b ^c Evershed, Nick (2024-11-03). "The chatbot optimisation game: can we trust AI web searches?". The Guardian. Guardian News & Media. Retrieved 2025-07-15.
^ Clay, Bruce (25 March 2025). "Answer engine optimization: 6 AI models you should optimize for". Search Engine Land.
^ DeBois, Pierre. "SEO vs. AISO: What AI Search Optimization Means for Brand Strategy". CMS Wire.

History

Industry applications

See also

References